期刊名称：International Journal on Computer Science and Engineering
印刷版ISSN：2229-5631
电子版ISSN：0975-3397
出版年度：2010
卷号：2
期号：2
页码：314-318
出版社：Engg Journals Publications
摘要：Association rule discovery from large databases is one of the tedious tasks in datamining.The process of frequent itemset mining, the first step in the mining of association rules, is a computational and IO intensive process necessitating repeated passes over the entire database. Sampling has been often suggested as an effective tool to reduce the size of the dataset operated at some cost to accuracy. Data mining literature presents with numerous sampling based approaches to speed up the process of Association Rule Mining(ARM).Sampling is one of the important and popular data reduction technique that is used to mine huge volume of data efficiently. Sampling can speed up the mining of association rules. In this paper, we provide an overview of existing sampling based association rule mining algorithms.
关键词：Datamining; sampling; Association rule mining; data reduction technique; Frequent pattern.
